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Performance Analysis and Optimization of a UAV-Enabled Two-Way Relaying Network Under FSMH, NC, and PNC Schemes

Authors :
Ruonan Zhang
Daosen Zhai
Bin Li
Xianzhen Guo
Source :
IEEE Internet of Things Journal. 8:17802-17816
Publication Year :
2021
Publisher :
Institute of Electrical and Electronics Engineers (IEEE), 2021.

Abstract

Unmanned aerial vehicles (UAVs) have played an important role in wireless communications due to the advantages such as highly controllable mobility in three-dimensional (3D) space, swift deployment, line-of-sight (LoS) aerial-ground links, and so on. In this paper, we consider a UAV-enabled two-way relaying system where the UAV relay assists the information exchange between two ground users (GUs) under three different schemes, i.e., four-slot multi-hopping (FSMH) without network coding (NC), three-slot NC and two-slot physical NC (PNC). Firstly, the capacity region of each scheme in this relaying system is analyzed. Then, we maximize the system average sum rate by jointly optimizing the time resources allocation, transmission powers of the transceivers, and the UAV trajectory subject to the constraints on UAV mobility and information causality under each scheme. To solve those problems, we propose an iterative algorithm by applying the successive convex approximation and block coordinate descent techniques. Specifically, the time resources allocation, transmission powers and the UAV trajectory are alternatively optimized in each iteration. In addition, the non-convex trajectory optimization problem is solved by successively solving an approximate convex optimization problem. To gain more insights, we also investigate the performance of those three schemes with symmetric and asymmetric traffic respectively by introducing a new traffic pattern constraint. Numerical results show that the proposed relaying schemes with moving relay can achieve great throughput gains as compared to the conventional scheme with static relay. The three relay schemes also show great performance heterogeneity under different traffic patterns.

Details

ISSN :
23722541
Volume :
8
Database :
OpenAIRE
Journal :
IEEE Internet of Things Journal
Accession number :
edsair.doi...........148e2ed21fb13d392b99fa270d081875